The effect of KIR-blocking on HLA-C immune response to SarsCov2

Introduction

Unusually high number of HLA-C recognition in CD8+ T cells
Responses could not be validated through TCR-specific confirmation assays
The Killer Immunoglobin Receptor (KIR) leads to false positive responses

Figure 1: KIR binding and blocking (Source: Biorender)

EMILIE:

The major histocompatibility complex (MHC), or HLA in humans, are well-known for their crucial role in assisting T cells in the induction of effective immune responses against antigens. While both HLA-A and -B have been widely studied for their interaction with T-cells and T-cell receptors (TCRs), much less is known about HLA-C - possibly due to the overall lower expression of HLA-C molecules.

However, newly published research has shown that HLA-C may pose a larger role in the immune response than first expected as an unusually high number of HLA-C recognition in CD8+ T cells was observed across cancer cohorts. A substantial portion of the identified responses could not be validated using a TCR-specific confirmation assay. This observation prompted the motivation for our study, aiming to distinguish between TCR-dependent and independent responses and hereby characterize TCR-specific and unspecific bindings of HLA-C molecules.

The study revealed that killer immunoglobulin receptors (KIR) bound to HLA-C restricted peptide-MHC complexes (pMHCs), leads to false-positive responses. The KIR receptor can be either inhibitory or activating and little is known about their role in T cells - despite being expressed at an average rate of 5%. The analysis made in this presentation therefore seek to clarify the understanding of the interactions involved in TCR-specific responses in HLA-C by employing a KIR antibody.

Materials and Methods - Project Flow Chart

Figure 2: Flowchart of the project

Materials and Methods

Data:

High-throughput experiment
Thousands of SarsCov2 peptides binding to T-cells
TCR-dependent or TCR-independent (i.e.: KIR-mediated)?

3 cohorts:

AP: Leukemia patients who have had COVID-19 (n = 12)
BS: Healthy nurses who have had COVID-19 (n = 17)
BC: Healthy donors (n = 15)

Methods:

DNA-barcoding: Tagging each peptide-HLA pair uniquely
Flow cytometry: Sorting T-cells based on TCR vs KIR binding

Materials and Methods - Barracoda data

	AP (N=13465)	BS (N=7840)	BC (N=10491)	Overall (N=31796)
KIR_blocking
1	7541 (56.0%)	4019 (51.3%)	7877 (75.1%)	19437 (61.1%)
0	5924 (44.0%)	3821 (48.7%)	2614 (24.9%)	12359 (38.9%)
log_fold_change
Mean (SD)	-1.15 (3.29)	-2.25 (3.95)	-1.49 (3.69)	-1.53 (3.62)
Median [Min, Max]	-0.182 [-13.4, 9.71]	-0.508 [-12.0, 8.64]	-0.313 [-12.4, 11.2]	-0.290 [-13.4, 11.2]
protein
ORF1	7239 (53.8%)	4447 (56.7%)	6103 (58.2%)	17789 (55.9%)
Nucleocapsid	707 (5.3%)	434 (5.5%)	548 (5.2%)	1689 (5.3%)
Spike	2619 (19.5%)	1581 (20.2%)	2062 (19.7%)	6262 (19.7%)
ORF6	68 (0.5%)	42 (0.5%)	65 (0.6%)	175 (0.6%)
Membrane	785 (5.8%)	465 (5.9%)	545 (5.2%)	1795 (5.6%)
ORF3	540 (4.0%)	345 (4.4%)	467 (4.5%)	1352 (4.3%)
ORF7	288 (2.1%)	175 (2.2%)	227 (2.2%)	690 (2.2%)
Envelope	119 (0.9%)	73 (0.9%)	91 (0.9%)	283 (0.9%)
ORF10	119 (0.9%)	73 (0.9%)	91 (0.9%)	283 (0.9%)
ORF8	322 (2.4%)	205 (2.6%)	292 (2.8%)	819 (2.6%)
Unknown	659 (4.9%)	0 (0%)	0 (0%)	659 (2.1%)
HLA
HLA-C04:01	300 (2.2%)	600 (7.7%)	2400 (22.9%)	3300 (10.4%)
HLA-C06:02	2695 (20.0%)	1086 (13.9%)	1164 (11.1%)	4945 (15.6%)
HLA-C07:01	4014 (29.8%)	2950 (37.6%)	2655 (25.3%)	9619 (30.3%)
HLA-C07:02	6456 (47.9%)	3204 (40.9%)	4272 (40.7%)	13932 (43.8%)

Table 1: Barracoda data

Figure 3: Protein representation accross the 4 HLA-C subtypes

~ 32 000 bar-codes (patient-HLA-peptide combinations)

44 patients
4 HLA types
11 protein types

Results - Filtering only significant responses

The number of observations reduced drastically during wrangling:

Figure 4: Volcano plot of all responses in joined dataset

Original: 31796
w. Flowjo: 22819
Significant: 542

Results - Paired boxblot

Paired data to compare TCR-dependent and TCR-independent responses:

This further reduced the dataset size:

Original: 31796
Significant: 542
Paired: 22
- 11 pairs
  - 1 normal
  - 1 KIR-blocked

Results - Bubble plot - paired

\[ Est. Freq = \left( \frac{count_{barcode}}{count_{total}} \cdot 100 \% \right) \cdot PE \]

Figure 6: Responses across pMHC multimers in the paired dataset

The fraction of T cells recognising the specified peptide
C0602 is a true response
AP cohort may have lower KIR expression due to pathology

EMILIE:

we extracted peptides that had shown a significant response for the paired data. The distribution of responses across the HLA-C allotypes are combined with the KIR blocking condition and response counts. The estimated frequency indicates the fraction of T cells that only recognises that specific peptide and was calculated earlier as:

The plot shows us that the C0602 group has no change from KIR blocking, which points to it being a true response binding to TCR. In the C0701 and 02 groups we see a fall in response size for all observed responses in the BS cohort. This implies that we do indeed remove false positive responses by KIR-blocking. Interestingly, we do not see this tendency in the AP cohort with hematological patients. This could be based on the pathology of the cohort, that individuals with chronic illnesses and cancer have a tendency of lower KIR expression on the cell surface

we extracted peptides that had shown a significant response for the paired data. The distribution of responses across the HLA-C allotypes are combined with the KIR blocking condition and response counts.

The plot shows us that the C0602 group has no change from KIR blocking, which points to it being a true response binding to TCR. In the C0701 and 02 groups we see a fall in response size for all observed responses in the BS cohort. This implies that we do indeed remove false positive responses by KIR-blocking. Interestingly, we do not see this tendency in the AP cohort with hematological patients. This could be based on the pathology of the cohort, that individuals with chronic illnesses and cancer have a tendency of lower KIR expression on the cell surface

Results - Bubble plot - unpaired

Figure 7: Responses across pMHC multimers in the unpaired dataset

BC cohort show significant response for C0401
False positives are removed in BS cohort for C0602
C0701 and C0702 show inconsistent responses

EMILIE:

Plot is for both paired and non-paired samples across all cohorts. For C0401, only the BC cohort shows significant responses in both KIR blocked and non blocked samples. C0602, the BS cohort shows a significant decrease in the amount of significant responses after KIR blocking. KIR blocking removes responses as intended. However, this could also be caused by the fact that these samples are non paired, potentially making the donor variation affect the repertoire of significant responses. For C0702 and C0701 we observe a tendency for the peptide specific responses as some are reduced after KIR blocking. However, in a few cases we also see an upregulation. This suggests that the KIR-blocking method may not be as robust as initially believed, introducing a level of complexity and prompting a closer examination of its reliability in certain contexts

In general there is a tendency that KIR blocking is seemingly less effective than expected, although we do see a fall in responses for specific HLA C allotypes across the cohorts.

(demonstrated a significant reduction in response by employing a KIR antibody - indicating that only the TCR-specific responses remained,)

The estimated frequency indicates the fraction of T cells that only recognises that specific peptide and was calculated earlier as: For C0401, only the BC cohort shows significant responses in both KIR blocked and non blocked samples. C0602, the BS cohort shows a significant decrease in the amount of significant responses after KIR blocking (lots of red dots, very few blue (obs maybe I changed the colors??)). This could also be caused by the fact that these samples are non paired, potentially making the donor variation affect the repertoire of significant responses. For C0702 and C0701 we see peptide specific responses that disappears after KIR blocking.

In general there is a tendency that KIR blocking is seemingly less effective than expected, although we do see a fall in responses for specific HLA C allotypes across the cohorts.

Discussion

KIR- blocking was showed to reduce the binding of pHMC
- corroborates TRC-independent binding
KIR-blocking was less efficient in reducing the binding of pHMC in the AP cohort
- hematological patients may have a lower KIR expression
Some results suggest that KIR-blocking is not as robust/reliable as expected

Limitations

The paired dataset was really small, hard to draw reliable conclusions
New info from this research group indicates that the KIR-antibody used in this experiment only blocked KIR-C1 but not -C2
- C0401 and C0601 are C2 ligands and were therefore not blocked
- This would explain the unreliable results, and variation between cohorts

MANON:

The registration of false positive responses were shown on a small subset of paired samples - it would require additional analysis in the future to confirm TCR specific response without the presence of non-blocked KIRs.

We could have made some changes to the threshold values to include more samples. We might lose some of the KIR blocked responses that falls beneath the threshold.

We have two sub types of KIR receptors, namely C1 and C2. However, just last week the phDs who made the dataset found that only C1 is blocked with the blocking antibody that we have. This means, that not all of them are blocked and some are still able to bind to pMHC. C0401 and C0601 are C2 ligands This makes us wonder whether all KIR receptors are truly blocked by the anti-KIR antibody used in this experiment